Biomedical subjects

E J Engelken

Publications and source records attributed to E J Engelken.

At least 19 recordsLinked to original sources

PubMed1992

Selecting a stimulus signal for linear systems analysis of the vestibulo-ocular reflex.

We evaluated 3 types of stimulus signals for use in estimating the transfer function of the vestibulo-ocular reflex. We used individual sine-wave, sum-of-sine, and pseudorandom stimuli. Five normal human subjects were tested 5 times each using each of the 3 stimulus types. Frequency domain techniques were used to estimate the transfer function at 0.01, 0.03, and 0.05 Hz. The most consistent estimates were obtained using individual sine-wave stimuli. The pseudorandom signal yielded the most variable estimates. A sum-of-sine stimulus composed of 3 sine-wave signals provided estimates slightly more variable than the individual sine-wave stimuli, but much less variable than the pseudorandom stimulus. The redundency of the sine and sum-of-sine stimuli seems to be an advantage by providing stable estimates of the transfer function in the presence of noise.

Adult↗

PubMed1991

A comparison of static and dynamic characteristics between rectus eye muscle and linear muscle model predictions.

The characteristics of a muscle model are analyzed using rectus eye muscle parameter values and compared to rectus eye muscle data. The muscle is modeled as a viscoelastic parallel combination connected to a parallel combination of active state tension generator, viscosity element, and length tension elastic element. Each of the elements is linear and their existence is supported with physiological evidence. The static and dynamic properties of the muscle model are compared to rectus eye muscle data. The length-tension characteristics of the model are in good agreement with the data within the operating region of the muscle. With the muscle model incorporated into a lever system to match the isotonic experiment paradigm, simulation results for this linear system yield a nonlinear force-velocity curve. Moreover, the family of force-velocity curves generated with different stimulus rates reported in the literature match the predictions of the model without parametric changes. The results of this paper are important in studies involving the oculomotor plant and oculomotor neural networks. Additionally, these results may be applicable to other muscles.

Isometric Contraction↗

PubMed1991

Relationships between manual reaction time and saccade latency in response to visual and auditory stimuli.

Manual reaction time (RT) responses were analyzed from seven human subjects. Responses were recorded using four kinds of target presentations: fixed visual target, moving visual target, fixed auditory target, and moving auditory target. Moving targets (moving in the horizontal plane) were presented at constant intensity and provided only a motion cue. Fixed targets "popped on" at the primary position and provided only an onset cue. RTs for the fixed and moving visual targets were 241.5 ms and 233.1 ms, respectively. The 8.4 ms (3.5%) advantage for the moving visual target over the fixed visual target was statistically significant, p less than 0.05. RT for the moving auditory target varied with target movement amplitude and ranged from 219 ms for 40 degree movements to 268 ms for 5 degree movements. For the fixed auditory target in the sagittal plane, average RT was 182.9 ms. Thus, sound-source motion detection was from 36 to 85 ms slower than sound onset detection, p less than 0.001. The RT results were compared to saccade latency measurements from an earlier study. Both RT and saccade latency showed the same dependency upon target movement amplitude. For small target displacements, saccade latencies for the moving auditory target were longer than for the moving visual target. The longer latencies for the moving auditory target are attributed to the increased processing time required to detect the sound-source motion.

Acoustic Stimulation↗

PubMed1991

Digitally calibrated eye movement measurement system.

A less expensive instrumentation alternative to record horizontal eye movements is presented in the form of a feasibility study. Currently, there are several techniques used to accurately measure eye position for research purposes. To implement these techniques, significant financial resources are required. The proposed technique costs less than $3000.00 and is based upon the limbus position technique. A linear charged coupled device (CCD) image array sensor and a biconvex lens are used to determine the position of the pupil. The self scanned CCD array is controlled by four analog clock signals generated from digital logic. The CCD video output signal is converted to a TTL compatible signal. The TTL signal is used to create a digital number based upon the limbus image formation upon the CCD pixels. This digital number is processed using standard signal acquisition techniques and is recorded on the hard drive disk of an IBM PC/AT compatible system. The C programming language is used to acquire the data and control calibration of the system. FORTRAN software is used to implement digital signal processing algorithms and estimate eye position.

Calibration↗

PubMed1991

Saccades simulated with rhesus monkey innervation data.

Extracellular single-unit data from the vicinity of the abducens nucleus from rhesus monkeys recorded during horizontal saccades are used as input to an updated oculomotor plant to simulate saccades to test the robustness of the model. Cells recorded from include: Long Lead Burst neurons, Medium Lead Burst neurons, and Burst Tonic neurons. Eye movement position data was collected using the magnetic coil technique. The oculomotor plant used in this study consists of the lateral and medial rectus muscle, and the eyeball. The muscles are modeled as a viscoelastic parallel combination connected to a parallel combination of active state tension generator, viscosity element and length tension elastic element. The eyeball is modeled as a sphere, connected to two parallel viscoelastic elements, connected in series. Each of the elements is linear. All parameters and initial conditions are estimated or directly measured from physiological data. The active state tension generator waveforms are the low-passed filtered motoneural signals. The extracellular single-unit data is used to drive the agonist portion of a neural circuit, consisting of burst, tonic and pause cells. The antagonist portion of the neural activity is based on previously reported characteristics. Simulation results for eye position and higher derivatives are in good agreement with the eye position data and the data derived estimates of higher derivatives.

Animals↗

PubMed1991

Optimization of an adaptive nonlinear filter for the analysis of nystagmus.

An adaptive nonlinear digital filter has been designed for the analysis of an eye-movement signal called nystagmus. Nystagmus is a bi-phasic signal consisting of a sequence of tracking eye movements called "slow-phase" interspersed with brief, high-velocity refixation movements called "fast-phase." The objective of the analysis is to separate the nystagmus signal into its fast- and slow-phase components. Specifically, the goal is to produce an evenly sampled estimate of slow-phase velocity (SPV) and an estimate of the peak fast-phase velocity. Classically this has been done using pattern recognition methods that exploit the fact that the fast-phase is a relatively short duration, high-velocity movement compared to the slow-phase. Unfortunately, these velocity and duration differences do not reliably separate the slow- and fast-phases under all conditions, especially when the signal is noisy. We have designed and built an adaptive nonlinear digital filter that easily outperforms the more complex pattern recognition algorithms. This new filter, called an Adaptive Asymmetrically Trimmed-Mean (AATM) filter, works under the assumption that, on the average, the eyes spend more time in slow-phase than in fast-phase. Thus, in any given data segment, most of the data samples are slow-phase samples. By analyzing the amplitude distribution of the data samples in the segment we can determine which of these samples are slow-phase. We used computer generated nystagmus signals contaminated with 3 levels of noise to evaluate the filter. The filter parameters were then optimized using Monte Carlo procedures producing an extremely robust analysis method.

Electronystagmography↗

PubMed1990

Periodic saccadic oscillations and tinnitus.

A man with essential hypertension developed stereotyped cycles of oscillopsia and bilateral "sparking" tinnitus. Eye movement recordings showed cycles of disconjugate opsoclonus, square-wave jerks, and saccadic dynamic overshoot disrupting stable fixation. Neuroimaging studies were normal. We postulate a lesion episodically disturbing saccade-related neurons and central auditory neurons in the pons.

Eye Movements↗

PubMed1990

A new approach to the analysis of nystagmus: an application for order-statistic filters.

A computer program has been designed for the analysis of nystagmus. This program employs a class of nonlinear digital filters called order-statistic (OS) filters. Two OS filters and one linear filter are used. First, the eye-movement signal is smoothed using a predictive finite-impulse response (FIR), median hybrid filter. Then the smoothed signal is processed by a linear band-limited differentiating filter to calculate eye velocity. And finally, the slow-phase velocity (SPV) envelope is extracted from the eye-velocity signal using an adaptive asymmetrically trimmed-mean filter. This approach yields an evenly sampled SPV estimate without resorting to the various interpolation or extrapolation schemes generally used. The adaptive filter estimates SPV based on the local statistical properties of the eye-velocity signal. The adaptive strategy works under the assumption that, on the average, the eyes spend more time in slow-phase than in fast-phase. No assumptions are made about the direction of the nystagmus or the nature of the stimulus used to elicit the nystagmus. This method eliminates all the usual threshold tests and decision logic common to other nystagmus analysis programs. The robust performance of OS filters and the use of adaptive filter structures totally eliminates the need to custom "tune" the program parameters for atypical data sets.

Aircraft↗

PubMed1990

Development of a non-linear smoothing filter for the processing of eye-movement signals.

The analysis of eye-movement (EM) signals poses problems for the designer of smoothing filters since many of the interesting types of EMs are bimodal. For example, optokinetic and/or vestibular stimulation results in an EM pattern called nystagmus consisting of alternating fast- and slow-phase components. Also, saccadic (refixation) EMs do not occur continuously, but are interspersed with periods of fixation. Conventional linear, low-pass filters (both finite impulse response (FIR) and infinite impulse response (IIR) types) smear the boundries between the fast- and slow-phases of nystagmus and the fixation and fast components of saccadic EMs. We have adapted a nonlinear smoothing filter (originally designed to optimize edge preservation in image processing applications) for the smoothing of EM signals. This filter is called a Predictive FIR-Median Hybrid (PFMH) filter. The PFMH filter operates on a moving window of data samples centered at the current point of interest. Several predictive FIR filters are applied to the "upper" and "lower" halves of the window and each are designed to predict the sample value at the center of the window. The median of these FIR filter outputs and the actual center data sample are taken as the PFMH filter output for each window position. By properly choosing the length and structure of the FIR subfilters, a PFMH filter can be designed to smooth a bimodal EM signal without blurring the boundries between the two signal components.

Electrooculography↗

PubMed1990

Additional developments in oculomotor plant modeling.

A new oculomotor plant is presented in this study using an updated third-order linear muscle model. The lateral and medial rectus muscle is modeled as a viscoelastic parallel combination connected to a parallel combination of active state tension generator, viscosity element and length tension elastic element. The eyeball is modeled as a sphere, connected to two parallel viscoelastic elements, connected in series. Each of the elements is linear. The static and dynamic properties of the muscle model are in good agreement with rectus muscle data. The length-tension characteristics of the model match the data within the operating region of the muscle. Simulation results for the muscle model yield hyperbolic shaped force-velocity curves that match the data very well. All parameters and initial conditions are estimated or directly measured from physiological data. The oculomotor plant is derived through direct programming state-space representation by Laplace variable analysis about the operating point or initial eye position. The form of the oculomotor plant makes this representation even more ideal than previous models for use in the development of more sensitive tests of oculomotor pathology and in the description of normal oculomotor function.

Elasticity↗

PubMed1990

Temporal characteristics of saccadic eye movements induced by auditory stimuli.

Records of horizontal saccadic eye movements made in response to auditory stimuli in the absence of any target related visual stimuli were obtained from two normal human subjects. A band-limiting derivative filter was convolved with records of eye position to obtain estimates of eye velocity. Eye position and velocity records were analyzed off-line to determine the characteristics of the audio-ocular response (AOR). The latency of the AOR decreased with increasing target movement amplitude. The AOR also exhibited lower peak velocity and longer duration than previously reported visually induced saccades. The time at peak velocity increased as saccade amplitude increased until for eye movements with amplitudes greater than 15 degrees, time at peak velocity showed little further increase. Finally, the AOR displayed a high incidence of dynamic overshoot for abducting movements of the right eye and a low incidence of dynamic overshoot for adducting movements of the right eye. System parameters estimated using system identification techniques indicate that the pulse portion of the active state tension driving the agonist muscle is of lower magnitude for auditory saccades than for visual saccades.

Eye Movements↗

PubMed1990

Sensitivity analysis of human oculomotor muscle model.

Sensitivity analysis is a procedure for examining the importance of model parameters with respect to the input or output of the model. Presented is a sensitivity analysis of a recently updated fourth order linear homeomorphic oculomotor model. Each muscle is modeled as a viscoelastic parallel combination connected to an active state tension generator, viscosity element and length tension element parallel combination. The eyeball is modeled as a sphere with a moment of inertia which is connected to two voight elements in series. The sensitivity analysis revealed the parameters of the model obtained from mathematical analysis are acceptable to be used as nominal parameters. Consequently, the analytical parameters can vary considerably while allowing the model to perform as empirical data predicts.

Elasticity↗

PubMed1989

Stochastic variables responsible for observed saccadic variability.

A new stochastic local feedback model of the horizontal saccadic system based on time optimal neural control within the superior colliculus has been previously described. This model uses a premotor neural circuit composed of burst, tonic, and pause cells and innervates a fourth order linear homeomorphic muscle plant. A sequence of saccades recorded from human subjects shows great variability in peak velocity, final position, and amount and type of post-saccadic behavior. This variability is duplicated in a sequence of simulated saccades through the use of random variables within the neural circuitry. The random variables are agonist burst cell magnitude, antagonist post inhibitory rebound burst magnitude and timing, and to a lesser extent muscle saturation magnitude. These four random variables are shown to cause all the observed variability in human saccades, including: trajectory profile, velocity profile, dynamic overshoot, and glissadic overshoot and undershoot.

Eye Movements↗

PubMed1989

Computer analysis of smooth pursuit eye movements.

Smooth-pursuit eye movements are analyzed using a system analysis approach. Frequency domain methods are used to factor the smooth-pursuit response into a linear component and a nonlinear or remnant component. The linear component is that part of the tracking response that is linearly related to the target movement; the remnant is the component remaining after the linear component is subtracted out. Tracking abnormalities that are not evident by inspection of the complete eye-movement record become obvious upon inspection of the remnant.

Computers↗

PubMed1989

Neurosignal analysis during saccadic eye movements.

An inverse method is developed to investigate the oculomotor neural control signal. The oculomotor plant is modeled with a fourth-order linear homeomorphic saccadic eye movement model. Parameter estimation is performed using a conjugate gradient search method which minimizes the integral of the absolute value of the error squared between the model and the data. Derivatives are computed using band-limited differentiation (BLD) techniques and the results are compared to derivatives computed using the two-point central difference method. Using the BLD technique allows for greater flexibility in choosing a cutoff frequency, provides true low-pass filtering above the cutoff frequency, and gives more consistent results than using the two-point central difference method. The input to the oculomotor plant model is computed. The input is a cumulative force consisting of the agonist and antagonist active state tensions and their respective rate-of-change terms. The agonist force is also determined by approximating the antagonist active state tension and removing if from the cumulative input force.

Electrooculography↗

PubMed1989

A linear muscle model predicts the hyperbolic force-velocity relationship.

A variety of different schemes have been reported in the literature for linearizing the force-velocity relationship observed in muscle, a dominant element in the muscle. This report extends assertions that a linear muscle system has force-velocity characteristics as described by Hill's hyperbolic equation, and that no linearization whatsoever is required. The muscle is modeled as a parallel combination of passive elasticity, and series elasticity connected to the parallel combination of active state tension generator, viscosity and length tension elasticity. Each of the elements are linear. Simulation solutions of this third-order system yield a hyperbolic shaped force-velocity curve using physiologically derived estimates, based on the oculomotor system, for the parameters of the muscle model.

Elasticity↗

PubMed1989

Agonist and antagonist muscle tension during horizontal saccadic eye movements.

Agonist and antagonist muscle tension simulations are reported for a fourth-order model of the oculomotor plant and active state tensions generated by a neural feedback model during horizontal saccadic eye movements. The lateral and medial rectus muscles are modeled as a parallel combination of passive elasticity, and series elasticity connected to a parallel combination of active state tension generator, viscosity element and elastic element. The eyeball is modeled as a sphere with moment of inertia connected to a viscosity element and an elastic element. The active state tension is generated by a low-pass filtered output from the neural burst circuit. The saccade generator is first-order time optimal and located in the superior colliculus. Agonist muscle tensions simulated with TUTSIM match the data extremely well. Antagonist muscle tension simulated with TUTSIM have an initial drop in tension, consistent with microelectrode predictions, and then a rise in muscle tension. The initial drop in antagonist muscle tension has not been reported in the literature because of band limitations of the force transducer used to record muscle tension.

Computer Simulation↗

PubMed1989

Saccadic eye movements in response to visual, auditory, and bisensory stimuli.

Saccadic eye movements were recorded and analyzed from eight normal human subjects. Various visual, auditory, and bisensory (visual and auditory) targets were tracked. Primary saccade latency, amplitude, duration, and peak velocity were calculated, as well as overall saccade duration (total time spent making saccades) and final eye position. Saccades made to bisensory targets employing a constant-intensity auditory component were not different from the pure visual target responses. Saccades to bisensory targets having an intermittent auditory component (with sound onset synchronous with the visual component) demonstrated a significant reduction in latency (11.3%) compared to the visual responses. The reduction occurred both for a fixed overhead sound source and for a sound source moving with the visual component. This result indicates that providing an auditory motion or localization cue alone does not reduce latency, but that a sound onset cue facilitates response time. No other response parameters were enhanced by using bisensory targets.

Acoustic Stimulation↗